Evidence map›Paper›PMID 25491199›Full record

ArticleJournal of translational medicine2014

Validation of a hemoglobin A1c model in patients with type 1 and type 2 diabetes and its use to go beyond the averaged relationship of hemoglobin A1c and mean glucose level.

Piotr Ladyzynski, Piotr Foltynski, Marianna I Bak, Stanislawa Sabalinska, Janusz Krzymien, Jerzy Kawiak

Open access · goldAbstract readValidation Study
In one paragraph

Article in Journal of translational medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Glycated Haemoglobin (HbAJournal of clinical medicine · 2024
    Review
  3. Evaluating HbAScientific reports · 2024
    Article
  4. Article
  5. Article
  6. Glycemic Status Assessment by the Latest Glucose Monitoring Technologies.International journal of molecular sciences · 2020
    Review
  7. Article
  8. Article
  9. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 1 country.

Piotr LadyzynskiNalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Trojdena street, 02-109, Warsaw, Poland. pladyzynski@ibib.waw.pl.
Piotr FoltynskiNalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Trojdena street, 02-109, Warsaw, Poland. pfoltynski@ibib.waw.pl.
Marianna I BakClinic and Department of Gastroenterology and Metabolic Diseases, Medical University of Warsaw, 1A Banacha street, 02-097, Warsaw, Poland. marianna@amwaw.edu.pl.
Stanislawa SabalinskaNalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Trojdena street, 02-109, Warsaw, Poland. ssabalinska@ibib.waw.pl.
Janusz KrzymienClinic and Department of Gastroenterology and Metabolic Diseases, Medical University of Warsaw, 1A Banacha street, 02-097, Warsaw, Poland. janusz.krzymien@wum.edu.pl.
Jerzy KawiakNalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, 4 Trojdena street, 02-109, Warsaw, Poland. jkawiak@ibib.waw.pl.
Institute of Biocybernetics and Biomedical Engineering · PLMedical University of Warsaw · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGlycated hemoglobin A1c (HbA1c) has been used as an index of glycemic control in the management, guidance, and clinical trials of diabetic patients for the past 35 years. The aim of this study was to validate the HbA1c model in patients with type 1 and type 2 diabetes and to use it to support interpretation of HbA1c in different clinical situations.

methodsThe HbA1c model was identified in 30 patients (15 with type 1 diabetes and 15 with type 2 diabetes) by estimating the overall glycation rate constant (k), based on results of continuous glucose monitoring. The model was validated by assessing its ability to predict HbA1c changes in cultures of erythrocytes in vitro and to reproduce results of the A1C-Derived Average Glucose (ADAG) study. The model was used to simulate the influence of different glucose profiles on HbA1c.

resultsThe mean k was equal to 1.296 ± 0.216 × 10(-9) l mmol(-1) s(-1) with no difference between type 1 and type 2 diabetes. The mean coefficient of variation of k was equal to 16.7%. The model predicted HbA1c levels in vitro with a mean absolute difference less than 0.3% (3.3 mmol/mol). It reproduced the linear relationship of HbA1c and mean glucose levels established in the ADAG study. The simulation experiments demonstrated that during periods of unstable glycemic control, glycemic profiles with the same mean glucose might result in much different HbA1c levels.

conclusionsPatients with type 1 and type 2 diabetes are characterized by the same mean value of k, but there is considerable interindividual variation in the relationship of HbA1c and mean glucose level. Results suggest that reciprocal changes in glycation rate and the life span of erythrocytes exist in a wide range of HbA1c values. Thus, for an average patient with diabetes, no modifications of parameters of the glycation model are required to obtain meaningful HbA1c predictions. Interpreting HbA1c as a measure of the mean glucose is fully justified only in the case of stable glycemia. The model and more frequent tests of HbA1c might be used to decrease ambiguity of interpreting HbA1c in terms of glycemic control.

Indexed as

AdolescentAdultBlood GlucoseDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2FemaleGlycated HemoglobinHumansMaleMiddle AgedYoung AdultBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, human

Identifiers

PMID25491199
PMCPMC4268801
OpenAlexW2134949105

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.